def makePlot(self, dirname, m, index, luminosity):
if self._data == None:
return
myStackList = []
# expected
for i in range(0, len(self._expectedList)):
myRHWU = RootHistoWithUncertainties(self._expectedList[i])
myRHWU.addShapeUncertaintyRelative(
"syst",
th1Plus=self._expectedListSystUp[i],
th1Minus=self._expectedListSystDown[i])
myRHWU.makeFlowBinsVisible()
if self._expectedLabelList[i] == "QCD":
myHisto = histograms.Histo(myRHWU,
self._expectedLabelList[i],
legendLabel=_legendLabelQCD)
elif self._expectedLabelList[i] == "Embedding":
myHisto = histograms.Histo(myRHWU,
self._expectedLabelList[i],
legendLabel=_legendLabelEmbedding)
elif self._expectedLabelList[i] == "EWKfakes":
myHisto = histograms.Histo(myRHWU,
self._expectedLabelList[i],
legendLabel=_legendLabelEWKFakes)
else:
myHisto = histograms.Histo(myRHWU, self._expectedLabelList[i])
myHisto.setIsDataMC(isData=False, isMC=True)
myStackList.append(myHisto)
# data
myRHWU = RootHistoWithUncertainties(self._data)
myRHWU.makeFlowBinsVisible()
myHisto = histograms.Histo(myRHWU, "Data")
myHisto.setIsDataMC(isData=True, isMC=False)
myStackList.insert(0, myHisto)
# Make plot
myStackPlot = plots.DataMCPlot2(myStackList)
myStackPlot.setLuminosity(luminosity)
myStackPlot.setEnergy("%d" % self._config.OptionSqrtS)
myStackPlot.setDefaultStyles()
myParams = {}
myParams["ylabel"] = "Events"
myParams["log"] = True
myParams["cmsTextPosition"] = "right"
myParams["opts"] = {"ymin": 0.9}
myParams["opts2"] = {"ymin": 0.3, "ymax": 1.7}
#myParams["moveLegend"] = {"dx": -0.08, "dy": -0.12, "dh": 0.1} # for MC EWK+tt
#myParams["moveLegend"] = {"dx": -0.15, "dy": -0.12, "dh":0.05} # for data-driven
myParams["moveLegend"] = {
"dx": -0.53,
"dy": -0.52,
"dh": 0.05
} # for data-driven
myParams["ratioMoveLegend"] = {"dx": -0.51, "dy": 0.03}
drawPlot(
myStackPlot, "%s/DataDrivenCtrlPlot_M%d_%02d_SelectionFlow" %
(dirname, m, index), **myParams)
def makePlot(self, dirname, m, index, luminosity):
if self._data == None:
return
myStackList = []
# expected
for i in range(0,len(self._expectedList)):
myRHWU = RootHistoWithUncertainties(self._expectedList[i])
myRHWU.addShapeUncertaintyRelative("syst", th1Plus=self._expectedListSystUp[i], th1Minus=self._expectedListSystDown[i])
myRHWU.makeFlowBinsVisible()
if self._expectedLabelList[i] == "QCD":
myHisto = histograms.Histo(myRHWU, self._expectedLabelList[i], legendLabel=_legendLabelQCD)
elif self._expectedLabelList[i] == "QCDdata":
myHisto = histograms.Histo(myRHWU, self._expectedLabelList[i], legendLabel=_legendLabelQCDdata)
elif self._expectedLabelList[i] == "Embedding":
myHisto = histograms.Histo(myRHWU, self._expectedLabelList[i], legendLabel=_legendLabelEmbedding)
elif self._expectedLabelList[i] == "EWKfakes":
myHisto = histograms.Histo(myRHWU, self._expectedLabelList[i], legendLabel=_legendLabelEWKFakes)
else:
myHisto = histograms.Histo(myRHWU, self._expectedLabelList[i])
myHisto.setIsDataMC(isData=False, isMC=True)
myStackList.append(myHisto)
# data
myRHWU = RootHistoWithUncertainties(self._data)
myRHWU.makeFlowBinsVisible()
myHisto = histograms.Histo(myRHWU, "Data")
myHisto.setIsDataMC(isData=True, isMC=False)
myStackList.insert(0, myHisto)
# Make plot
myStackPlot = plots.DataMCPlot2(myStackList)
myStackPlot.setLuminosity(luminosity)
myStackPlot.setEnergy("%d"%self._config.OptionSqrtS)
myStackPlot.setDefaultStyles()
myParams = {}
myParams["ylabel"] = "Events"
myParams["log"] = True
myParams["cmsTextPosition"] = "right"
myParams["opts"] = {"ymin": 0.9}
myParams["opts2"] = {"ymin": 0.3, "ymax":1.7}
#myParams["moveLegend"] = {"dx": -0.08, "dy": -0.12, "dh": 0.1} # for MC EWK+tt
#myParams["moveLegend"] = {"dx": -0.15, "dy": -0.12, "dh":0.05} # for data-driven
myParams["moveLegend"] = {"dx": -0.53, "dy": -0.52, "dh":0.05} # for data-driven
myParams["ratioMoveLegend"] = {"dx": -0.51, "dy": 0.03}
drawPlot(myStackPlot, "%s/DataDrivenCtrlPlot_M%d_%02d_SelectionFlow"%(dirname,m,index), **myParams)
def printSummaryInfo(columnNames, myNuisanceInfo, cachedHistos, hObs, m,
luminosity, opts):
config = aux.load_module(opts.settings)
def addOrReplace(dictionary, key, newItem):
if not key in dictionary.keys():
dictionary[key] = newItem.Clone()
else:
dictionary[key].Add(newItem)
def getHisto(cachedHistos, name):
for h in cachedHistos:
if h.GetName() == name:
return h
raise Exception("Cannot find histogram '%s'!" % name)
# Create for each column a root histo with uncertainties
myDict = OrderedDict()
myTotal = None
# Loop over columns (datasets)
for c in columnNames:
# Bugfix to prevent crashing with blacklisted datasets
if c in config.Blacklist:
continue
hRate = aux.Clone(getHisto(cachedHistos, c))
myRHWU = RootHistoWithUncertainties(hRate)
for n in myNuisanceInfo:
# Add shape uncertainties
if n["name"] != "observation" and n[
"distribution"] == "shape" and n[
c] == "1" and not "statBin" in n["name"]:
hUp = aux.Clone(
getHisto(cachedHistos, "%s_%sUp" % (c, n["name"])))
hDown = aux.Clone(
getHisto(cachedHistos, "%s_%sDown" % (c, n["name"])))
myRHWU.addShapeUncertaintyFromVariation(n["name"], hUp, hDown)
# Add constant uncertainties
elif n["name"] != "observation" and n["name"] != "rate" and n[
"name"] != "process" and n[c] != "-" and n[
c] != "1" and not "statBin" in n[
"name"] and not "BinByBin" in n["name"]:
diffUp = 0.0
diffDown = 0.0
if "/" in n[c]:
mySplit = n[c].split("/")
diffDown = float(mySplit[0]) - 1.0
diffUp = float(mySplit[1]) - 1.0
else:
diffDown = float(n[c]) - 1.0
diffUp = float(n[c]) - 1.0
myRHWU.addNormalizationUncertaintyRelative(
n["name"], diffUp, diffDown)
# Store column info
_myBr = 0.01
myAddToTotalStatus = False
if c.startswith("HH") or c.startswith("CMS_Hptntj_HH"):
myRHWU.Scale(_myBr**2)
addOrReplace(myDict, "Hp", myRHWU)
elif c.startswith("HW") or c.startswith("CMS_Hptntj_HW"):
myRHWU.Scale(2.0 * _myBr * (1.0 - _myBr))
addOrReplace(myDict, "Hp", myRHWU)
elif c.startswith("Hp") or c.startswith("CMS_Hptntj_Hp"):
addOrReplace(myDict, "Hp", myRHWU)
elif c == "EWK_Tau" or c.startswith("CMS_Hptntj_EWK_Tau"):
addOrReplace(myDict, "EWKtau", myRHWU)
myAddToTotalStatus = True
elif c.endswith("genuinetau"):
addOrReplace(myDict, c.replace("CMS_Hptntj_", ""), myRHWU)
myAddToTotalStatus = True
elif c.endswith("faketau"):
addOrReplace(myDict, "EWKfakes", myRHWU)
myAddToTotalStatus = True
elif c.startswith("QCD") or c.startswith("CMS_Hptntj_QCD"):
addOrReplace(myDict, "QCD", myRHWU)
myAddToTotalStatus = True
else:
myDict[c] = myRHWU
myAddToTotalStatus = True
if myAddToTotalStatus:
if myTotal == None:
myTotal = myRHWU.Clone()
else:
myTotal.Add(myRHWU.Clone())
myDict["Totalbkg"] = myTotal
# Make table
print "\nEvent yields:"
myTotal = None
for item in myDict.keys():
if myDict[item] != None:
myDict[item].makeFlowBinsVisible()
rate = myDict[item].getRate()
stat = myDict[item].getRateStatUncertainty()
(systUp, systDown) = myDict[item].getRateSystUncertainty()
#myDict[item].Debug()
print "%11s: %.1f +- %.1f (stat.) + %.1f - %.1f (syst.)" % (
item, rate, stat, systUp, systDown)
print "Observation: %d\n\n" % hObs.Integral(0, hObs.GetNbinsX() + 2)
def setTailFitUncToStat(rhwu):
tailfitNames = filter(lambda n: "_TailFit_" in n,
rhwu.getShapeUncertaintyNames())
rhwu.setShapeUncertaintiesAsStatistical(tailfitNames)
#rhwu.printUncertainties()
#print rhwu.getShapeUncertaintiesAsStatistical()
return rhwu
myLogList = [False, True]
for l in myLogList:
# Create post fit shape
myStackList = []
if "QCD" in myDict.keys():
myHisto = histograms.Histo(
setTailFitUncToStat(myDict["QCD"].Clone()),
"QCD",
legendLabel=ControlPlotMaker._legendLabelQCD)
myHisto.setIsDataMC(isData=False, isMC=True)
myStackList.append(myHisto)
if "EWKtau" in myDict.keys():
myHisto = histograms.Histo(
setTailFitUncToStat(myDict["EWKtau"].Clone()),
"Embedding",
legendLabel=ControlPlotMaker._legendLabelEmbedding)
myHisto.setIsDataMC(isData=False, isMC=True)
myStackList.append(myHisto)
for c in myDict.keys():
if c.endswith("genuinetau"):
histoID = c.replace("CMS_Hptntj_",
"").replace("_genuinetau", "")
lookupTable = { # Map column name to style in plots.py
"tt": "TT",
"W": "WJets",
"t": "SingleTop",
"DY": "DYJetsToLL",
"VV": "Diboson",
"tt_and_singleTop": "TTandSingleTop",
"EWK": "EWK"
}
histoString = lookupTable[histoID]
myHisto = histograms.Histo(
setTailFitUncToStat(myDict[c].Clone()),
histoString,
legendLabel=c.replace("CMS_Hptntj_", ""))
myHisto.setIsDataMC(isData=False, isMC=True)
myStackList.append(myHisto)
if "EWKfakes" in myDict.keys() and myDict["EWKfakes"] != None:
myHisto = histograms.Histo(
myDict["EWKfakes"].Clone(),
"EWKfakes",
legendLabel=ControlPlotMaker._legendLabelEWKFakes)
myHisto.setIsDataMC(isData=False, isMC=True)
myStackList.append(myHisto)
myBlindedStatus = not opts.unblinded
myBlindingString = None
hObsLocal = aux.Clone(hObs)
if myBlindedStatus:
myBlindingString = "%d-%d GeV" % (hObs.GetXaxis().GetBinLowEdge(1),
hObs.GetXaxis().GetBinUpEdge(
hObs.GetNbinsX()))
for i in range(0, hObs.GetNbinsX()):
hObsLocal.SetBinContent(i, -1.0)
hObsLocal.SetBinError(i, 0.0)
# Add data
myDataHisto = histograms.Histo(hObsLocal, "Data")
myDataHisto.setIsDataMC(isData=True, isMC=False)
myStackList.insert(0, myDataHisto)
# Add signal
mySignalLabel = "TTToHplus_M%d" % float(m)
if float(m) > 179:
mySignalLabel = "HplusTB_M%d" % float(m)
myHisto = histograms.Histo(myDict["Hp"].Clone(), mySignalLabel)
myHisto.setIsDataMC(isData=False, isMC=True)
myStackList.insert(1, myHisto)
# Make plot
myStackPlot = plots.DataMCPlot2(myStackList)
myStackPlot.setLuminosity(luminosity)
#myStackPlot.setEnergy("%d"%self._config.OptionSqrtS)
myStackPlot.setDefaultStyles()
myParams = {}
if myBlindedStatus:
myParams["blindingRangeString"] = myBlindingString
myParams["cmsTextPosition"] = "right"
myParams["ratio"] = True
myParams["ratioType"] = "errorScale"
myParams["ratioYlabel"] = "Data/Bkg. "
myParams["stackMCHistograms"] = True
myParams["addMCUncertainty"] = True
myParams["addLuminosityText"] = True
myParams["moveLegend"] = {"dx": -0.14, "dy": -0.10}
myParams["ratioErrorOptions"] = {"numeratorStatSyst": False}
myParams["ratioCreateLegend"] = True
#myParams["ratioMoveLegend"] = {"dx": -0.51, "dy": 0.03}
myParams["ratioMoveLegend"] = {"dx": -0.06, "dy": -0.1}
myParams["opts2"] = {"ymin": 0.0, "ymax": 2.5}
myParams["xlabel"] = "m_{T} (GeV)"
#if l:
# myParams["ylabel"] = "< Events / bin >"
#else:
myParams["ylabel"] = "Events / 20 GeV"
a = hObsLocal.GetXaxis().GetBinWidth(1)
b = hObsLocal.GetXaxis().GetBinWidth(hObsLocal.GetNbinsX())
#if abs(a-b) < 0.0001:
#myParams["ylabel"] += "%d GeV"%a
#else:
#myParams["ylabel"] += "%d-%d GeV"%(a,b)
#myParams["divideByBinWidth"] = l
myParams["log"] = l
myPlotName = "PostTailFitShape_M%d" % float(m)
if l:
# scale ymin by 20 in order to compare the rebinned mT with same y-scale
# ymax(factor) takes care of max automatically
myParams["opts"] = {"ymin": 20 * 1e-5}
else:
myParams["opts"] = {"ymin": 0.0}
myPlotName += "_Linear"
plots.drawPlot(myStackPlot, myPlotName, **myParams)
def printSummaryInfo(columnNames, myNuisanceInfo, cachedHistos, hObs, m, luminosity, opts):
config = aux.load_module(opts.settings)
def addOrReplace(dictionary, key, newItem):
if not key in dictionary.keys():
dictionary[key] = newItem.Clone()
else:
dictionary[key].Add(newItem)
def getHisto(cachedHistos,name):
for h in cachedHistos:
if h.GetName() == name:
return h
raise Exception("Cannot find histogram '%s'!"%name)
# Create for each column a root histo with uncertainties
myDict = OrderedDict()
myTotal = None
# Loop over columns (datasets)
for c in columnNames:
# Bugfix to prevent crashing with blacklisted datasets
if c in config.Blacklist:
continue
hRate = aux.Clone(getHisto(cachedHistos, c))
myRHWU = RootHistoWithUncertainties(hRate)
for n in myNuisanceInfo:
# Add shape uncertainties
if n["name"] != "observation" and n["distribution"] == "shape" and n[c] == "1" and not "statBin" in n["name"]:
hUp = aux.Clone(getHisto(cachedHistos, "%s_%sUp"%(c,n["name"])))
hDown = aux.Clone(getHisto(cachedHistos, "%s_%sDown"%(c,n["name"])))
myRHWU.addShapeUncertaintyFromVariation(n["name"], hUp, hDown)
# Add constant uncertainties
elif n["name"] != "observation" and n["name"] != "rate" and n["name"] != "process" and n[c] != "-" and n[c] != "1" and not "statBin" in n["name"] and not "BinByBin" in n["name"]:
diffUp = 0.0
diffDown = 0.0
if "/" in n[c]:
mySplit = n[c].split("/")
diffDown = float(mySplit[0])-1.0
diffUp = float(mySplit[1])-1.0
else:
diffDown = float(n[c])-1.0
diffUp = float(n[c])-1.0
myRHWU.addNormalizationUncertaintyRelative(n["name"], diffUp, diffDown)
# Store column info
_myBr = 0.01
myAddToTotalStatus = False
if c.startswith("HH") or c.startswith("CMS_Hptntj_HH"):
myRHWU.Scale(_myBr**2)
addOrReplace(myDict, "Hp", myRHWU)
elif c.startswith("HW") or c.startswith("CMS_Hptntj_HW"):
myRHWU.Scale(2.0*_myBr*(1.0-_myBr))
addOrReplace(myDict, "Hp", myRHWU)
elif c.startswith("Hp") or c.startswith("CMS_Hptntj_Hp"):
addOrReplace(myDict, "Hp", myRHWU)
elif c == "EWK_Tau" or c.startswith("CMS_Hptntj_EWK_Tau"):
addOrReplace(myDict, "EWKtau", myRHWU)
myAddToTotalStatus = True
elif c.endswith("genuinetau"):
addOrReplace(myDict, c.replace("CMS_Hptntj_",""), myRHWU)
myAddToTotalStatus = True
elif c.endswith("faketau"):
addOrReplace(myDict, "EWKfakes", myRHWU)
myAddToTotalStatus = True
elif c.startswith("QCD") or c.startswith("CMS_Hptntj_QCD"):
addOrReplace(myDict, "QCD", myRHWU)
myAddToTotalStatus = True
else:
myDict[c] = myRHWU
myAddToTotalStatus = True
if myAddToTotalStatus:
if myTotal == None:
myTotal = myRHWU.Clone()
else:
myTotal.Add(myRHWU.Clone())
myDict["Totalbkg"] = myTotal
# Make table
print "\nEvent yields:"
myTotal = None
for item in myDict.keys():
if myDict[item] != None:
myDict[item].makeFlowBinsVisible()
rate = myDict[item].getRate()
stat = myDict[item].getRateStatUncertainty()
(systUp,systDown) = myDict[item].getRateSystUncertainty()
#myDict[item].Debug()
print "%11s: %.1f +- %.1f (stat.) + %.1f - %.1f (syst.)"%(item,rate,stat,systUp,systDown)
print "Observation: %d\n\n"%hObs.Integral(0,hObs.GetNbinsX()+2)
def setTailFitUncToStat(rhwu):
tailfitNames = filter(lambda n: "_TailFit_" in n, rhwu.getShapeUncertaintyNames())
rhwu.setShapeUncertaintiesAsStatistical(tailfitNames)
#rhwu.printUncertainties()
#print rhwu.getShapeUncertaintiesAsStatistical()
return rhwu
myLogList = [False,True]
for l in myLogList:
# Create post-tailfit shape
myStackList = []
if "QCD" in myDict.keys():
myHisto = histograms.Histo(setTailFitUncToStat(myDict["QCD"].Clone()),"QCD",legendLabel=ControlPlotMaker._legendLabelQCD)
myHisto.setIsDataMC(isData=False, isMC=True)
myStackList.append(myHisto)
if "EWKtau" in myDict.keys():
myHisto = histograms.Histo(setTailFitUncToStat(myDict["EWKtau"].Clone()),"Embedding",legendLabel=ControlPlotMaker._legendLabelEmbedding)
myHisto.setIsDataMC(isData=False, isMC=True)
myStackList.append(myHisto)
for c in myDict.keys():
if "CMS_Hptntj" in c:
histoID = c.replace("CMS_Hptntj_","").replace("_CMS_Hptntj","")
lookupTable = { # Map column name to style in plots.py
"ttbar": "TT",
"W": "WJets",
"t": "SingleTop",
"DY": "DYJetsToLL",
"VV": "Diboson",
"singleTop": "SingleTop",
"QCDandFakeTau": "QCDdata",
"EWK": "EWK"
}
histoString = lookupTable[histoID]
myHisto = histograms.Histo(setTailFitUncToStat(myDict[c].Clone()),histoString,legendLabel=c.replace("CMS_Hptntj_",""))
myHisto.setIsDataMC(isData=False, isMC=True)
myStackList.append(myHisto)
if "EWKfakes" in myDict.keys() and myDict["EWKfakes"] != None:
myHisto = histograms.Histo(myDict["EWKfakes"].Clone(),"EWKfakes",legendLabel=ControlPlotMaker._legendLabelEWKFakes)
myHisto.setIsDataMC(isData=False, isMC=True)
myStackList.append(myHisto)
myBlindedStatus = not opts.unblinded
myBlindingString = None
hObsLocal = aux.Clone(hObs)
if myBlindedStatus:
myBlindingString = "%d-%d GeV"%(hObs.GetXaxis().GetBinLowEdge(1),hObs.GetXaxis().GetBinUpEdge(hObs.GetNbinsX()))
for i in range(0, hObs.GetNbinsX()):
hObsLocal.SetBinContent(i, -1.0)
hObsLocal.SetBinError(i, 0.0)
# Add data
myDataHisto = histograms.Histo(hObsLocal,"Data")
myDataHisto.setIsDataMC(isData=True, isMC=False)
myStackList.insert(0, myDataHisto)
# Add signal
mySignalLabel = "TTToHplus_M%d"%float(m)
if float(m) > 179:
mySignalLabel = "HplusTB_M%d"%float(m)
myHisto = histograms.Histo(myDict["Hp"].Clone(),mySignalLabel)
myHisto.setIsDataMC(isData=False, isMC=True)
myStackList.insert(1, myHisto)
# Make plot
myStackPlot = plots.DataMCPlot2(myStackList)
myStackPlot.setLuminosity(luminosity)
#myStackPlot.setEnergy("%d"%self._config.OptionSqrtS)
myStackPlot.setDefaultStyles()
myParams = {}
if myBlindedStatus:
myParams["blindingRangeString"] = myBlindingString
myParams["cmsTextPosition"] = "right"
myParams["ratio"] = True
myParams["ratioType"] = "errorScale"
myParams["ratioYlabel"] = "Data/Bkg. "
myParams["stackMCHistograms"] = True
myParams["addMCUncertainty"] = True
myParams["addLuminosityText"] = True
myParams["moveLegend"] = {"dx": -0.14, "dy": -0.10}
myParams["ratioErrorOptions"] = {"numeratorStatSyst": False}
myParams["ratioCreateLegend"] = True
#myParams["ratioMoveLegend"] = {"dx": -0.51, "dy": 0.03}
myParams["ratioMoveLegend"] = {"dx": -0.06, "dy": -0.1}
myParams["opts2"] = {"ymin": 0.0, "ymax": 2.0}
myParams["xlabel"] = "m_{T} (GeV)"
#if l:
# myParams["ylabel"] = "< Events / bin >"
#else:
myParams["ylabel"] = "Events / bin"
myParams["divideByBinWidth"] = True
a = hObsLocal.GetXaxis().GetBinWidth(1)
b = hObsLocal.GetXaxis().GetBinWidth(hObsLocal.GetNbinsX())
myParams["log"] = l
myPlotName = "postTailFitShape_M%d"%float(m)
if l:
# scale ymin by 20 in order to compare the rebinned mT with same y-scale
# ymax(factor) takes care of max automatically
myParams["opts"] = {"ymin": 1e-4, "ymaxfactor": 15, "xmax": 800}
else:
myParams["opts"] = {"ymin": 0.0, "xmax": 800}
myPlotName += "_linear"
plots.drawPlot(myStackPlot, myPlotName, **myParams)